NAME
README - General Information about WordNet::SenseRelate::AllWords
OVERVIEW
This module carries out word sense disambiguation (WSD), which is the
process of selcting the correct sense for a word in a given context. The
correct sense is selected from a sense inventory which lists the
possible meanings of a word. This module uses the WordNet lexical
database as it's sense inventory.
SYNOPSIS
use WordNet::SenseRelate::AllWords;
use WordNet::QueryData;
use WordNet::Tools;
my $qd = WordNet::QueryData->new;
my $wntools = WordNet::Tools->new($qd);
my %options = (wordnet => $qd,
wntools => $wntools,
measure => 'WordNet::Similarity::lesk'
);
my $obj = WordNet::SenseRelate::AllWords->new(%options);
my @context = qw/when in the course of human events/;
my @res = $obj->disambiguate (window => 3,
scheme => 'normal',
tagged => 0,
context => [@context]);
print join (' ', @res), "\n";
CONTENTS
When the distribution is unpacked, several subdirectories are created:
/lib
This directory contains the Perl modules that do the actual work of
disambiguation. By default, these files are installed into
/usr/local/lib/perl5/site_perl/PERL_VERSION (where PERL_VERSION is
the version of Perl you are using). See the INSTALL file for more
information.
/utils
This directoy contains a number of scripts that let you run word
sense disambiguation experiments and reformat data.
These scripts will be install when 'make install' is run. By
default, these files are installed into your /usr/local/bin
directory. See the INSTALL file for more information. The scripts in
this directory are:
wsd.pl
This very useful script can be used to disambiguate a file of
words. It is discussed in greater detail later in this document.
semcor-reformat.pl
This script will reformat a Semcor file so that it can be used
as input to wsd.pl
scorer2-format.pl
This script will reformat the output of wsd.pl so that it can be
used as input to the Senseval scorer2 program.
Each of these scripts has detailed documentation. Run perldoc on a
file to see the detailed documentation; for example, 'perldoc
wsd.pl' shows the documentation for wsd.pl.
/doc
This directory contains all of the *pod files used to document the
system. These are processed via pod2text and the output of this is
placed in the top level directory, although these top level text
files should be considered read only.
/samples
This directory contains examples of the different formats of data
that are supported by this package. It also contains a sample
stoplist. There is a README file in the directory that describes the
contents in more detail.
/t This directory contains test scripts. These scripts are run when you
execute 'make test'.
/web
This directory contains the allwords web server and interface. There
are detailed README and INSTALL instructions within this directory.
Installing the web interface is optional, and is separate from
installing the main package.
DESCRIPTION
Words can have multiple meanings or senses. For example, the word
*glass* in WordNet [1] has seven senses as a noun and five senses as a
verb. Glass can mean a clear solid, a container for drinking, the
quantity a drinking container will hold, etc. WSD is the process of
selecting the correct sense of a word when that word occurs in a
specific context. For example, in the sentence, "the window is made of
glass", the correct sense of glass is the first sense, a clear solid.
WordNet::SenseRelate::AllWords extends a word sense disambiguation
algorithm described by Pedersen, Banerjee, and Patwardhan [2] by making
it disambiguate all words in text. The previous version of the algorithm
was intended for lexical sample data, which means that a single word in
a context is designated as the target word and is the only word to be
disambiguated. By contrast, WordNet::SenseRelate::AllWords will assign a
sense to every word known to WordNet that appears in a context.
Prior to execution of the algorithm, we remove any word that is not
known to WordNet, and any word that appears in a stoplist. The input to
the algorithm is presumed to be a single sentence where non-WordNet
words and stoplisted words have been removed.
WordNet::SenseRelate::AllWords does not cross sentence boundaries when
carrying out disambiguation.
Algorithm
for each word w in sentence
disambiguate-single-word (w)
disambiguate-single-word (w)
for each sense s_ti of target word t, where i=0..N
let score_i = 0
for each word w_j in context_window
next if j = t
for each sense s_jk of w_j
temp-score_k = relatedness (s_ti, s_jk)
best-score = max temp-score
if best-score > pairScore
score_i = score_i + best-score
return s_ti s.t. score_i > score_j for all j in
{s_t0, ..., s_tN} and score_i > contextScore
The Context Window
The size of the context window can be specified by the user. A context
window of size 3 means that the context window will consist of three
words, including the target word. Thus, the three words would be the
word to the left of the target word, the target word itself, and the
word to the right of the target word. The algorithm will expand the
context window so that the three words will be words known to WordNet
(the algorithm is unable to disambiguate words unknown to WordNet). For
example, if the word 'the', occurs in the context window to the left of
the target word, then the window will be expanded by one word to the
left.
If the window size is an even number, then there will be one more word
to the left of the target word than to the right. For example, if the
window size is 4, there will be two words to the left of the target word
and one word to the right.
Note that the context window will only include words in the same
sentence as the target word. If, for example, the target word is the
first word in the sentence, then there will be no words to left of the
target word in the context window regarless of the specified window
size.
The minimum window size is 2 because a smaller window mean that there
are no context words in the window. When the window size is 2, there is
no context to use for disambiguating the first word in a sentence. To
assign a sense number to that first word, the first sense of the word is
chosen (i.e., sense number 1). Sense number 1 is usually the most
frequent sense of a word.
Part of Speech Coercion
Certain measures of semantic similarity only work on noun-noun or
verb-verb pairs; therefore, the usefulness of these measures for WSD is
somewhat limited. As a way of coping with this problem,
WordNet::SenseRelate::AllWords provides an option to "coerce" words in
the context window to be of the same part of speech as the target word.
When POS coercion is in effect, if the target word is a noun, then
WordNet::SenseRelate::AllWords will attempt to convert non-nouns in the
context window to noun forms of the same word. For example, if the
target word is a noun and the verb *love* occurs in the window, the
module might convert that word to the noun *love*.
WordNet::SenseRelate::AllWords first uses the validForms method from
WordNet::QueryData to find any valid forms of the word being coerced
that are of the desired part of speech. In the case of part of speech
tagged text, the POS tags are discarded. If validForms did not return
any forms of the desired part of speech, then the derived forms relation
in WordNet is used to find possible forms of the word. If neither of
these methods returned usable forms, then no further attempt is made to
coerce the word to be the desired part of speech.
Tracing/Debugging
Several different levels of trace output are available. The trace level
can be specified as a command-line option to wsd.pl or as a parameter to
the WordNet::SenseRelate::AllWords module.
Trace Levels
The trace levels are:
1 Show the context window for each pass through the algorithm.
2 Display winning score for each pass (i.e., for each target word).
4 Display the non-zero scores for each sense of each target
word (overrides 2).
8 Display the non-zero values from the semantic relatedness measures.
16 Show the zero values as well when combined with either 4 or 8.
When not used with 4 or 8, this has no effect.
32 Display traces from the semantic relatedness module.
Different trace levels can be combined to achieve the desired behavior.
For example, by specifying a trace level of 3, both level 1 and level 2
traces are generated (i.e., the context window will be shown along with
the winning score for each pass).
Using wsd.pl
The wsd.pl script provides an easy method of performing disambiguation
from the command line. The text to be disambiguated is read from a file
provided by the user on the command line.
Output
The output of wsd.pl is simply the disambiguated words. The output will
be in the form word#part_of_speech#sense_number. The part of speech will
be one of 'n' for noun, 'v' for verb, 'a' for adjective, or 'r' for
adverb. Words from other parts of speech are not disambiguated and are
not found in WordNet. The sense number will be a WordNet sense number.
WordNet sense numbers are assigned by frequency, so sense 1 of a word is
more common than sense 2, etc.
Sometimes when a word is disambiguated, a "different" but synonymous
word will be found in the output. This is not a bug but is a consequence
of how WordNet works. The word sense returned will always be the first
word sense in a synset (synonym set) to which the original word belongs.
Usage
wsd.pl --context FILE --format FORMAT [--scheme SCHEME] [--type MEASURE]
[--config FILE] [--stoplist FILE] [--window INT] [--contextScore NUM]
[--pairScore NUM] [--outfile FILE] [--trace INT] [--silent] | --help |
--version
The format option specifies one of the three different formats supported
by wsd.pl. The three formats are:
raw Raw text that is not part of speech tagged. This text should be
formatted so that there is one sentence per line, one line per
sentence. For example:
Red cars are faster than white cars.
However, white cars are less expensive.
Punctuation will be ignored, and compounds known to WordNet will be
identified automatically (e.g., 'winston churchill' will be
recognized as a compound and converted to winston_churchill).
tagged
Tagged text has been Part of Speech tagged (using the Penn TreeBank
tag set). This text should be formatted so that there is one
sentence per line, one line per sentence. For example:
Red/JJ cars/NNS are/VBP faster/RBR than/IN white/JJ cars/NNS ./.
However/RB white/JJ cars/NNS are/VBP less/RBR expensive/JJ ./.
Words that are not tagged will be ignored even if they are known to
WordNet. Punctuation is ignored. Compounds will not be automatically
identified, they must be specified by the user (e.g.,
winston_churchill/NNP, red_tape/NNS).
wntagged
Identical to tagged text, except that the part of speech tags are
from the WordNet tag set, which limits them to 'n', 'v', 'a', or
'r', for nouns, verbs, adjectives and adverbs. This text should be
formatted so that there is one sentence per line, one line per
sentence. For example:
red#a car#n be#v faster#r than white#a car#n .
however white#a car#n be#v less#r expensive#a .
Words that are not tagged will be ignored even if they are known to
WordNet. Punctuation is ignored. Compounds will not be automatically
identified, they must be specified by the user (e.g.,
winston_churchill#n, red_tape#n).
Additionally, no attempt will be made to search for other valid
forms of the words in the input. For example, if 'dogs#n' is in the
input, the program will not attempt to use other forms such as
'dog#n'.
The different options and parameters for wsd.pl are discussed in detail
in the documentation for wsd.pl. Run 'perldoc wsd.pl' to view the
documentation.
Usage Examples
1. wsd.pl --context input.txt --format raw
2. wsd.pl --trace 3 --context input.txt --format raw
3. wsd.pl --trace 3 --context input.txt --window 4 --format raw
Using the Disambiguation Module
The WordNet::SenseRelate::AllWords Perl module can be used in other Perl
programs to perform word sense disambiguation.
Example
use WordNet::SenseRelate::AllWords;
use WordNet::QueryData;
use WordNet::Tools;
my $qd = WordNet::QueryData->new;
my $wntools = WordNet::Tools->new($qd);
my %options = (wordnet => $qd,
wntools => $wntools,
measure => 'WordNet::Similarity::lesk'
);
my $obj = WordNet::SenseRelate::AllWords->new(%options);
my @context = qw/when in the course of human events/;
my @res = $obj->disambiguate (window => 3,
scheme => 'normal',
tagged => 0,
context => [@context]);
print join (' ', @res), "\n";
The context parameter to disambiguate() specifies a set of words to
disambiguate. The function treats the context as one sentence. To
disambiguate multiple sentences, make a call to disambiguate() for each
sentence.
The usage of the disambiguation module is discussed in detail in the
documentation for the module. Run 'perldoc
WordNet::SenseRelate::AllWords' or 'man WordNet::SenseRelate::AllWords'
(after installing the module) to view the documentation. To view the
documentation before installing the module, run 'perldoc
lib/WordNet/SenseRelate/AllWords.pm'.
REFERENCES
1. Christiane Fellbaum (editor) (1998) WordNet: an Electronic Lexical
Database. MIT Press.
2. Ted Pedersen, Satanjeev Banerjee, and Siddharth Patwardhan (2005)
Maximizing Semantic Relatedness to Perform Word Sense
Disambiguation, University of Minnesota Supercomputing Institute
Research Report UMSI 2005/25, March.
3. Jason Michelizzi (2005), Semantic Relatedness Applied to All Words
Sense Disambiguation, Master of Science Thesis, Department of
Computer Science, University of Minnesota, Duluth, July, 2005.
SEE ALSO
WordNet::SenseRelate::AllWords
The main web page for SenseRelate is :
L
There are several mailing lists for SenseRelate :
L
L
L
AUTHORS
Ted Pedersen
Varada Kolhatkar
Jason Michelizzi
Last updated by :
# $Id: README,v 1.19 2008/09/15 23:42:05 kvarada Exp $
COPYRIGHT
Copyright (C) 2004-2008 by Ted Pedersen, Varada Kolhatkar, Jason
Michelizzi
This program is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation; either version 2 of the License, or (at your
option) any later version.
This program is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
Public License for more details.